By Aske Plaat, Jaap van den Herik, Walter Kosters
Read or Download Advances in Computer Games: 14th International Conference, ACG 2015, Leiden, The Netherlands, July 1-3, 2015, Revised Selected Papers PDF
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This quantity supplies an updated assessment of theoretical and experimental tools of learning the digital band constitution. a variety of formalisms for particular calculations and lots of info of worthy purposes, rather to alloys and semiconductors, are provided. The contributions conceal the subsequent matters: alloy part diagrams, density functionals; disordered alloys; heavy fermions; impurities in metals and semiconductors; linearize band constitution calculations; magnetism in alloys; sleek idea of alloy band constitution; momentum densities in metals and alloys; photoemission; quasi-particles and homes of semiconductors; the recursion strategy and delivery homes of crystals and quasi-crystals.
This e-book constitutes the completely refereed post-conference lawsuits of the fifteenth foreign assembly on DNA Computing, DNA15, held in Fayetteville, AR, united states, in June 2009. The sixteen revised complete papers provided have been rigorously chosen in the course of rounds of reviewing and development from 38 submissions.
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Extra resources for Advances in Computer Games: 14th International Conference, ACG 2015, Leiden, The Netherlands, July 1-3, 2015, Revised Selected Papers
Intell. AI Games 2(4), 303–309 (2010) 3. : Eﬀect of LGRF on the playing strength agains gnugo. Website 15 June 2012. org/msg05060. html. Accessed 09 March 2015 4. : PACHI: state of the art open source go program. , Plaat, A. ) ACG 2011. LNCS, vol. 7168, pp. 24–38. Springer, Heidelberg (2012) 5. : Stochastic gradient tricks. -R. ) Neural Networks, Tricks of the Trade, Reloaded. Lecture Notes in Computer Science, vol. 7700, pp. 430–445. Springer, Heidelberg (2012) Adaptive Playouts in Monte-Carlo Tree Search 11 6.
Simulation-based approach to general game playing. In: AAAI, pp. 259–264 (2008) 11. : Learning simulation control in general game-playing agents. In: AAAI (2010) 12. : Mathematical games. Sci. Am. 230, 106–108 (1974) 13. : Monte-Carlo tree search and rapid action value estimation in computer go. Artif. Intell. 175(11), 1856–1875 (2011) 14. : General game playing: overview of the AAAI competition. AI Mag. 26(2), 62–72 (2005) 15. 0: a pattern-based MCTS hex player. In: Computers and Games - 8th International Conference, CG 2013, Yokohama, Japan, 13–15 August 2013, Revised Selected Papers, pp.
Their work also showed that even simple evaluation functions can lead to better performance. However, they found that this technique did not work on every game. They ran experiments on Chinese checkers and the card game Heart but obtained no signiﬁcant improvement. Our Work. For CDC, we use as the heuristic evaluation function the weighted material sum, namely the diﬀerence of the total piece weights between the player and the oppo‐ nent. The piece weights are listed in Table 1. The heuristic evaluations are then scaled to [–1, 1] by a sigmoid function.